Why I Did Not Publish Welcome to the Machine

Three years ago, I began drafting a book called Welcome to the Machine, a Primer on AI for Marketers. A marketing-centric look at the machine learning revolution, people seemed excited. I drafted public articles and interviews illustrating some of the themes and even completed the first draft. Yet, I elected to stop working on the project. Why?

The book didn’t add anything to the marketing body of knowledge. There was no theoretical evolution, no hypothesis to argue. Instead, it simply documented how AI was impacting various aspects of the marketing discipline in 2019. 

In reviewing the chapters, it felt like a series of tools that took manual tasks and automated them. You wrote about power tools, I thought to myself. The book wasn’t special, I concluded. If I couldn’t add something new to the conversation, it was probably best to simply table it.

Publishing this book about marketing AI would have restored some industry influence, but that was not my goal. There are enough talking heads building generic thought “leadership” based on marketing trends. Heck, I’ve done the same thing myself.

I’ve published six books including three business books, two of which the world could probably forget in a heartbeat. The third, Welcome to the Fifth Estate, I still reflect upon with fondness. It added something to the conversation with its media theory. Adding something to the conversation – real value – is what matters to me.

Have Something to Say

It wasn’t enjoyable talking about Twitter for the 200th time, and I see the same thing with marketing AI. There is a need to educate people about this next generation of tools, and I have some friends who are doing this very well right now. 

Books are labor intense. Believe it or not, while drafting one seems like an accomplishment, the project is still not 50 percent finished. You have to edit the book numerous times, fix its weaknesses, rewrite portions, and then hopefully complete final edits. Then if you actually want people to read the book, you better have a marketing plan in place. Marketing the book in its own right is at least a third of your effort.

These hundreds of hours make pennies on the dollar in a direct P&L sense. Rare is the author who gets rich off their books themselves. You really need a book that sells close to the hundred thousand mark to make cash.  

Like musicians, most authors make significant money off of their appearances and private consulting. And of course, then you are talking about capitalizing on the influence your book creates, which is another effort in its own right

Knowing what I know today, publishing requires a deep-seated belief that the ideas contained need to be shared with the marketplace or that they represent a substantial work of art. Otherwise, why bother?

Books Can Make You Influential

Certain types of influencers need to publish periodic books to serve as capstones or chevrons of their market statures. However, I think there is an equal argument that you can create significant influence without writing a book. In fact, I still help others achieve this kind of influence.

With that in mind, if I want to build influence again book-writing would not be my first approach unless I had a novel idea best explained using that format.

Ironically, the book I ended up publishing after drafting Welcome to the Machine was a photo book of Washington, DC civil rights protests during the Trump era. I published that as more of a personal project, something so that my book backers and family would have forever to remember the very real attack on civil freedoms that occurred. That meant something to me individually, and as a Livingston (my Great Grand Uncle started the Anti-Defamation League).

Domain-specific AI in the marketing realm still strikes me as an algorithmic power tool that produces a recommendation, analytics, or action much faster than a human could. Now, this broad brush stroke oversimplifies the omnipresent impacts made by machine learning. It is not meant to minimize the incredible progress marketing AI has made building complete customer journeys, eliminating rote tasks like spell checks and video optimization, and much more.

The incredible speed and power that AI has made in this field as well as others is certainly remarkable. We have seen better evolutions and easier methods to approach the business of marketing, from finding images on stock sites to placing automatically evolving and placing ads in micro-markets by the social network or media. 

But marketing is still about compelling people to take buying actions. In that sense, marketing AI makes it easier but it is not changing the fundamentals, at least not yet. Instead, it is eliminating human error and making those that use AI faster and better at interacting with their prospects.

Conclusion

Maybe the inner creative in me simply got bored with the topic as a subject to pursue relentlessly every single day for hours every day. In the end, AI at its most powerful deep-learning level is still an algorithmic pursuit towards a singular goal. It saves incredible amounts of time and resources. But it lacks emotional intelligence, creativity, context, and depth.

Once I understood marketing AI, I appreciated it. In hindsight, the exercise left me more fascinated with the creative expressions humans would make with these new marketing power tools. That in its own right is another story for another day, perhaps even a book.

But the Welcome to the Machine conversation was one for others to lead. I know this is true after reading AI 2041 by Kai-Fu Lee and Chen Quifan’s general treatise on where machine learning is going. This book did such a wonderful job explaining AI’s strengths and weaknesses, it helped me realize how flawed my original take on this topic was.

I do want to thank all the people who contributed time to that effort. While the book was never published, I still published many articles and interviews from that research on Medium here. I hope it was enough and that you don’t feel burned by spending some of your time with me.